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COMP24111 Course Unit Overview

COMP24111 Course Unit Overview. Ke Chen and Tingting Mu http://syllabus.cs.manchester.ac.uk/ugt/COMP24111 /. COMP24111 Introduction to Machine Learning. Introduction. The Big Picture: Introductory machine learning course unit for 2 nd Year UG students

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COMP24111 Course Unit Overview

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  1. COMP24111Course Unit Overview Ke Chen and Tingting Mu http://syllabus.cs.manchester.ac.uk/ugt/COMP24111/ COMP24111 Introduction to Machine Learning

  2. Introduction COMP24111 Introduction to Machine Learning The Big Picture: • Introductory machine learning course unit for 2nd Year UG students • Reasonable Math background required • Matlab programming language used in lab exercises • Contact time: 20-hour lectures and 10-hour lab sessions • 10 two-hour lectures (11:00-13:00, Tuesday, Weeks 1-5 & Weeks 7-11) • 5 two-hour lab sessions (Weeks 1, 3, 5, 8 and 10) • Self-revision and back-log clearing lab marking in Week 12 • No lecture but providing the self-revision materials • A two-hour lab session added for completing lab ex. Marking (last chance!)

  3. Lecture and Lab COMP24111 Introduction to Machine Learning Part I (Weeks 1-5): Dr.Tingting Mu • Five lectures • Week 1: Machine learning basics, Nearest neighbour classifier • Week 2-3: Linear classification and regression • Week 4: Support vector machine • Week 5: Neural network and deep learning • Three lab sessions • Week 1: Lab Ex. 1 (Matlab programming) and marking • Week 3: Lab Ex. 2 help desk • Week 5: Lab Ex. 2 marking

  4. Lecture and Lab COMP24111 Introduction to Machine Learning Part II (Weeks 7-12): Dr. Ke Chen • Five lectures • Week 7: Generative models and naïve Bayes • Week 8: Clustering analysis basics • Week 9: K-mean clustering • Week 10: Hierarchical and ensemble clustering • Week 11: Cluster validation • Three lab sessions • Week 8: Lab Ex. 3 help desk • Week 10: Lab Ex. 3 marking • Week 12: Clearing back-log (last chance for marking any of your Lab Ex.)

  5. Assessment Method • Examination (60%) Three sections: all questions are compulsory • Section A: MCQs (30 marks); Q1-15 (Part I), Q16-30 (Part II) • Section B: Questions pertaining to Part I (15 marks) • Section C: Questions pertaining to Part II (15 marks) • Lab Exercises (40%) • Three lab exercises (Lab ex 2 & 3, the same deadline for all the groups) • Exercise 1 (10 marks): Matlab programming (marked in your 1stlab) • Exercise 2 (15 marks): Face recognition (deadline: 11:00, 25th Oct. 2018) • Exercise 3 (15 marks): Spam filtering (deadline: 11:00, 29th Nov. 2018) COMP24111 Introduction to Machine Learning

  6. Organise Your Time for Lab Work Advice: To complete Ex 2 and Ex 3, you need to revise the knowledge learned in the lectures, and practise the knowledge through experiments. You have three weeks to work on each exercise. You should keep in mind that you will NOT be able to complete Ex 2 and 3 by working only in the allocated lab sessions. Start as early as possible! COMP24111 Introduction to Machine Learning • Exercise 1: • Start as early as possible (start after this lecture). • Exercise 2,3: • Start as early as possible (start after the lecture in week 2 for ex2, start after the lecture in week 7 for ex3). • Fully utilise the help desk session, be prepared in advance (week 3 for ex2, week 8 for ex3)

  7. Lab Help and Marking COMP24111 Introduction to Machine Learning • Marking (Week 1,5,10,12): • Write your computer number in whiteboard when you need marking. • All the lab ex marking takes place in Lab and will be marked by TAs under the supervision of lab supervisors (Part I: T. T. Mu, Part II: K. Chen). • Remember to register attendance if not marked. • Help Desk (Week 3, 8): • Write your computer number in whiteboard when you have questions. • If there is no question in the queue, TA can do marking. But please note that this is NOT prioritised in help desk. • Remember to register attendance.

  8. Other Information COMP24111 Introduction to Machine Learning • The teaching page (URL: syllabus.cs.manchester.ac.uk/ugt/COMP24111/) contains all the information regarding this CU, e.g. lecture notes, lab ex. specification/deadline/policy, non-assessed ex, self-revision slides, FAQ, …… • Read the FAQ page available on the teaching page (URL: http://syllabus.cs.manchester.ac.uk/ugt/COMP24111/materials/COMP24111-FAQ.pdf) before asking questions. Recommended textbooks [EA] E. Alpaydin, Introduction to Machine Learning (3rd Ed.), MIT Press, 2014. (core) [KPM] K. P. Murphy, Machine learning: A Probabilistic Perspective, MIT Press, 2012. [CMB] C. M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.

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